from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="onnx", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time onnx. For instance, a speedup of 2 means that onnx is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.129 | 0.280 | 0.000 | 0.002 | -1 | 1 | 0.663 | 17.337 | 0.047 | 0.663 | 0.123 | 0.123 | See | See |
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.002 | 0.000 | 0.024 | -1 | 1 | 1.000 | 0.313 | 0.002 | 1.000 | 0.075 | 0.075 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.824 | 0.029 | 0.000 | 0.003 | -1 | 5 | 0.757 | 17.081 | 0.178 | 0.757 | 0.165 | 0.165 | See | See |
| 3 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | 0.000 | 0.023 | -1 | 5 | 1.000 | 0.314 | 0.004 | 1.000 | 0.074 | 0.074 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.107 | 0.091 | 0.000 | 0.002 | 1 | 100 | 0.882 | 17.063 | 0.054 | 0.882 | 0.123 | 0.123 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 100 | 1.000 | 0.317 | 0.006 | 1.000 | 0.060 | 0.060 | See | See |
| 6 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.871 | 0.159 | 0.000 | 0.003 | -1 | 100 | 0.882 | 17.302 | 0.138 | 0.882 | 0.166 | 0.166 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.002 | 0.000 | 0.024 | -1 | 100 | 1.000 | 0.313 | 0.003 | 1.000 | 0.077 | 0.077 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.059 | 0.014 | 0.000 | 0.002 | 1 | 5 | 0.757 | 17.465 | 0.175 | 0.757 | 0.118 | 0.118 | See | See |
| 9 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.020 | 0.001 | 0.000 | 0.020 | 1 | 5 | 1.000 | 0.307 | 0.008 | 1.000 | 0.065 | 0.065 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.199 | 0.005 | 0.001 | 0.001 | 1 | 1 | 0.663 | 17.547 | 0.110 | 0.663 | 0.068 | 0.068 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 1 | 1.000 | 0.319 | 0.005 | 1.000 | 0.059 | 0.059 | See | See |
| 12 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.807 | 0.034 | 0.000 | 0.002 | -1 | 1 | 0.896 | 3.776 | 0.014 | 0.896 | 0.479 | 0.479 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.004 | 0.000 | 0.006 | -1 | 1 | 1.000 | 0.238 | 0.003 | 1.000 | 0.024 | 0.024 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.847 | 0.101 | 0.000 | 0.003 | -1 | 5 | 0.922 | 3.692 | 0.024 | 0.922 | 0.771 | 0.771 | See | See |
| 15 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.002 | 0.000 | 0.007 | -1 | 5 | 1.000 | 0.236 | 0.003 | 1.000 | 0.028 | 0.028 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.965 | 0.012 | 0.000 | 0.002 | 1 | 100 | 0.929 | 3.762 | 0.012 | 0.929 | 0.522 | 0.522 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.239 | 0.004 | 1.000 | 0.012 | 0.012 | See | See |
| 18 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.757 | 0.043 | 0.000 | 0.003 | -1 | 100 | 0.929 | 3.756 | 0.010 | 0.929 | 0.734 | 0.734 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.003 | 0.000 | 0.006 | -1 | 100 | 1.000 | 0.239 | 0.004 | 1.000 | 0.025 | 0.025 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.940 | 0.005 | 0.000 | 0.002 | 1 | 5 | 0.922 | 3.730 | 0.009 | 0.922 | 0.520 | 0.520 | See | See |
| 21 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 1.000 | 0.239 | 0.004 | 1.000 | 0.012 | 0.012 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.094 | 0.008 | 0.000 | 0.001 | 1 | 1 | 0.896 | 3.778 | 0.007 | 0.896 | 0.289 | 0.289 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.240 | 0.005 | 1.000 | 0.008 | 0.008 | See | See |
KNeighborsClassifier_kd_tree¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.822 | 0.946 | 0.000 | 0.001 | -1 | 1 | 0.929 | 105.283 | 0.000 | 0.929 | 0.008 | 0.008 | See | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.002 | 0.000 | 0.003 | -1 | 1 | 1.000 | 2.619 | 0.163 | 1.000 | 0.001 | 0.001 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.982 | 0.301 | 0.000 | 0.001 | -1 | 5 | 0.946 | 105.170 | 0.000 | 0.946 | 0.009 | 0.009 | See | See |
| 3 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 1.000 | 2.616 | 0.180 | 1.000 | 0.001 | 0.001 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.425 | 0.347 | 0.000 | 0.005 | 1 | 100 | 0.951 | 107.860 | 0.000 | 0.951 | 0.050 | 0.050 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 1.000 | 2.609 | 0.146 | 1.000 | 0.001 | 0.001 | See | See |
| 6 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.143 | 0.243 | 0.000 | 0.003 | -1 | 100 | 0.951 | 106.993 | 0.000 | 0.951 | 0.029 | 0.029 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 1.000 | 2.627 | 0.141 | 1.000 | 0.002 | 0.002 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.581 | 0.122 | 0.000 | 0.002 | 1 | 5 | 0.946 | 106.126 | 0.000 | 0.946 | 0.015 | 0.015 | See | See |
| 9 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.001 | 0.000 | 0.002 | 1 | 5 | 1.000 | 2.604 | 0.078 | 1.000 | 0.001 | 0.001 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.873 | 0.101 | 0.000 | 0.001 | 1 | 1 | 0.929 | 105.090 | 0.000 | 0.929 | 0.008 | 0.008 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 2.596 | 0.120 | 1.000 | 0.000 | 0.000 | See | See |
| 12 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.026 | 0.013 | 0.001 | 0.000 | -1 | 1 | 0.891 | 0.045 | 0.013 | 0.891 | 0.582 | 0.607 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.001 | 0.000 | 0.002 | -1 | 1 | 1.000 | 0.005 | 0.000 | 1.000 | 0.482 | 0.483 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.022 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.911 | 0.037 | 0.001 | 0.911 | 0.600 | 0.600 | See | See |
| 15 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 1.000 | 0.005 | 0.000 | 1.000 | 0.376 | 0.376 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.035 | 0.006 | 0.000 | 0.000 | 1 | 100 | 0.894 | 0.058 | 0.001 | 0.894 | 0.598 | 0.598 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.005 | 0.000 | 1.000 | 0.104 | 0.104 | See | See |
| 18 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.036 | 0.003 | 0.000 | 0.000 | -1 | 100 | 0.894 | 0.058 | 0.001 | 0.894 | 0.628 | 0.628 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 1.000 | 0.005 | 0.000 | 1.000 | 0.373 | 0.373 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.020 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.911 | 0.038 | 0.000 | 0.911 | 0.526 | 0.527 | See | See |
| 21 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.005 | 0.000 | 1.000 | 0.106 | 0.106 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.019 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.891 | 0.038 | 0.000 | 0.891 | 0.501 | 0.501 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.005 | 0.000 | 1.000 | 0.107 | 0.107 | See | See |
HistGradientBoostingClassifier_best¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: learning_rate=0.01, n_iter_no_change=10.0, max_leaf_nodes=100.0, max_bins=255.0, min_samples_leaf=100.0, max_iter=300.0.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 0.107 | 0.001 | 300 | 0.007 | 0.000 | 0.824 | 0.496 | 0.023 | 0.824 | 0.215 | 0.216 | See | See |
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1 | 100 | 0.016 | 0.000 | 300 | 0.000 | 0.016 | 1.000 | 0.413 | 0.008 | 1.000 | 0.039 | 0.039 | See | See |